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- 저자 : Alhashmi, Asma A. (검색결과 4 건)
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Alamer Fahad Alhashmi,AlQwaizani Eptehal,Althagafy Khalid 한국탄소학회 2024 Carbon Letters Vol.34 No.1
Carbon-based materials, particularly graphite, have been extensively studied for their potential in fabricating flexible conductive fabrics with high electrical conductivity, which are attractive for wearable electronics. In this study, we investigated the effects of polar solvents, graphite concentration, and temperature on the electrical properties of conductive cotton fabrics. Our results show that the type of polar solvent and graphite concentration strongly influence the electrical conductivity of the fabrics. By controlling the graphite concentration, a wide range of conductive cotton fabrics with different conductivity values can be produced. Additionally, temperature resistance studies revealed that the fabrics exhibit both semiconductor and metallic behavior in the temperature range from room temperature to 160 °C. These interesting properties make the conductive cotton fabrics suitable for use as electrical components in circuits with resistive and inductive loads. Furthermore, we fabricated a supercapacitor with electrodes based on dispersed graphite and an electrolyte of sodium chloride salt dissolved in deionized water. Our findings suggest that conductive cotton fabrics have great potential for use in high-performance wearable electronics and energy storage devices.
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A Model of Artificial Intelligence in Cyber Security of SCADA to Enhance Public Safety in UAE
Omar Abdulrahmanal Alattas Alhashmi,Mohd Faizal Abdullah,Raihana Syahirah Abdullah International Journal of Computer ScienceNetwork S 2023 International journal of computer science and netw Vol.23 No.2
The UAE government has set its sights on creating a smart, electronic-based government system that utilizes AI. The country's collaboration with India aims to bring substantial returns through AI innovation, with a target of over $20 billion in the coming years. To achieve this goal, the UAE launched its AI strategy in 2017, focused on improving performance in key sectors and becoming a leader in AI investment. To ensure public safety as the role of AI in government grows, the country is working on developing integrated cyber security solutions for SCADA systems. A questionnaire-based study was conducted, using the AI IQ Threat Scale to measure the variables in the research model. The sample consisted of 200 individuals from the UAE government, private sector, and academia, and data was collected through online surveys and analyzed using descriptive statistics and structural equation modeling. The results indicate that the AI IQ Threat Scale was effective in measuring the four main attacks and defense applications of AI. Additionally, the study reveals that AI governance and cyber defense have a positive impact on the resilience of AI systems. This study makes a valuable contribution to the UAE government's efforts to remain at the forefront of AI and technology exploitation. The results emphasize the need for appropriate evaluation models to ensure a resilient economy and improved public safety in the face of automation. The findings can inform future AI governance and cyber defense strategies for the UAE and other countries.
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Cybersecurity Threats and Countermeasures of the Smart Home Ecosystem
Darem, Abdulbasit,Alhashmi, Asma A.,Jemal, H.A. International Journal of Computer ScienceNetwork S 2022 International journal of computer science and netw Vol.22 No.3
The tremendous growth of the Internet of things is unbelievable. Many IoT devices have emerged on the market over the last decade. This has made our everyday life easier inside our homes. The technology used at home has changed significantly over the past several decades, leading to what is known today as the smart home. However, this growth has also brought new challenges to our home security and privacy. With the smart home becoming more mainstream, cybersecurity issues have become a fundamental concern. The smart home is an environment where heterogeneous devices and appliances are interconnected through the Internet of Things (IoT) to provide smart services to residents. These services include home climate control, energy management, video on demand, music on-demand, remote healthcare, remote control, and other similar services in a ubiquitous manner. Smart home devices can be controlled via the Internet using smartphones. However, connecting smart home appliances to wireless networks and the Internet makes individuals vulnerable to malicious attacks. Remote access within the same environment or over the Internet requires an effective access control mechanism. This paper intends to shed light on how smart home devices are working as well as the type of security and privacy threats of the smart home. It also illustrated the types of authentication methods that can be used with smart home devices. In addition, a comparison of Smart home IoT-based security protocols was presented along with a security countermeasure that can be used in a smart home environment. Finally, a few open problems were mentioned as future research directions for researchers.
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A Knowledge-based Model for Semantic Oriented Contextual Advertising
( Mohammed Maree ),( Rami Hodrob ),( Mohammed Belkhatir ),( Saadat M. Alhashmi ) 한국인터넷정보학회 2020 KSII Transactions on Internet and Information Syst Vol.14 No.5
Proper and precise embedding of commercial ads within Webpages requires Ad-hoc analysis and understanding of their content. By the successful implementation of this step, both publishers and advertisers gain mutual benefits through increasing their revenues on the one hand, and improving user experience on the other. In this research work, we propose a novel multi-level context-based ads serving approach through which ads will be served at generic publisher websites based on their contextual relevance. In the proposed approach, knowledge encoded in domain-specific and generic semantic repositories is exploited in order to analyze and segment Webpages into sets of contextually-relevant segments. Semantically-enhanced indexes are also constructed to index ads based on their textual descriptions provided by advertisers. A modified cosine similarity matching algorithm is employed to embed each ad from the Ads repository into one or more contextually-relevant segments. In order to validate our proposal, we have implemented a prototype of an ad serving system with two datasets that consist of (11429 ads and 93 documents) and (11000 documents and 15 ads), respectively. To demonstrate the effectiveness of the proposed techniques, we experimentally tested the proposed method and compared the produced results against five baseline metrics that can be used in the context of ad serving systems. In addition, we compared the results produced by our system with other state-of-the-art models. Findings demonstrate that the accuracy of conventional ad matching techniques has improved by exploiting the proposed semantically-enhanced context-based ad serving model.
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